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1)  feature weighting
特征加权
1.
Analysis and improvement of feature weighting method TF·IDF in text categorization;
文本特征加权方法TF·IDF的分析与改进
2.
To weaken the effects of blur edges and much noise in infrared images,a novel approach on recognition for infrared images based on Gabor filters and feature weighting is presented in this paper.
针对红外图像边缘模糊、噪声较多的特点,文中提出一种新的基于Gabor滤波器和特征加权的红外图像识别方法。
3.
In this paper we focus our attention on the works in this field, which include four parts: an improved Gabor feature extraction algorithm based on feature weighting, infrared vehicle detection with Gabor filters and Support Vector Machines (SVM), vehicle clas.
包括基于特征加权的Gabor特征抽取算法:基于Gabor滤波器和SVM的红外车辆检测;一种简单的基于Gabor滤波器和边缘特征的车型识别算法:以及实用的基于特定方向的Gabor滤波器组参数设置方法。
2)  feature weight
特征加权
1.
Mixed fuzzy clustering analysis based on feature weights and its application in classification of flood disaster grade
基于特征加权的混合型模糊聚类分析及其在洪水灾害等级划分中的应用
2.
Study several common recognition algorithms,then advance a full-area feature weight template matching algorithm.
通过对现有常用的几种模板匹配算法的分析与研究,提出了一种全区域特征加权模板匹配识别算法,它是对特征加权的模板匹配算法的一种改进。
3.
In the Fuzzy c-Means algorithm, considering the particular contributions of different feature, a feature weight fuzzy clustering algorithm is introduced in this paper.
在FCM算法中,考虑到样本矢量中各维特征对模式分类的不同影响,本文引入一种基于特征加权的模糊聚类算法,该算法考虑了各维特征对分类的贡献不同,从而对数据进行了更有效的分类。
3)  feature weighted
特征加权
1.
Based on the fundamental theory of clustering analysis and fuzzy mathematics,the numerical and attributes characteristic samples of history flood were established,and the characteristic samples were analyzed on a basin by using feature weighted fuzzy clustering algorithm.
基于聚类分析和模糊数学的基本原理,对历史洪水建立属性和数值特征的洪水样本,并运用特征加权FCM算法对流域历史洪水特征样本进行聚类分析。
2.
Feature weighted is the general case of feature selection,which has better performance than(or at least has the same performance as) feature selection.
特征加权是特征选择的一般情况,它能更加细致地区分特征对结果影响的程度,往往能够获得比特征选择更好的或者至少相等的性能。
3.
In this paper,distance metric and feature weighted algorithms have been provided for pretreatment of data which are gathered in the network.
提出以距离度量和特征加权算法为基础,对网络中采集到的各种原始样本参数进行数据预处理,以便为故障诊断提供更加可靠、准确地输入参量。
4)  weighted feature
特征加权
5)  weighted feature
加权特征
1.
Possibility Fuzzy Clustering Approach with Weighted Features;
一种基于加权特征的可能模糊聚类方法
6)  weighted eigenface(WE)
特征脸加权
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